Cleaning uncertain data for top-k queries

@article{Mo2013CleaningUD,
  title={Cleaning uncertain data for top-k queries},
  author={Luyi Mo and Reynold Cheng and Xiang Li and David Wai-Lok Cheung and Xuan S. Yang},
  journal={2013 IEEE 29th International Conference on Data Engineering (ICDE)},
  year={2013},
  pages={134-145}
}
The information managed in emerging applications, such as sensor networks, location-based services, and data integration, is inherently imprecise. To handle data uncertainty, probabilistic databases have been recently developed. In this paper, we study how to quantify the ambiguity of answers returned by a probabilistic top-k query. We develop efficient algorithms to compute the quality of this query under the possible world semantics. We further address the cleaning of a probabilistic database… CONTINUE READING